# rayrender动态可视化 **Repository Path**: cubics29/rayender-dynamic-visualization ## Basic Information - **Project Name**: rayrender动态可视化 - **Description**: 利用rayrender动态可视化全球人口密度 - **Primary Language**: Unknown - **License**: Not specified - **Default Branch**: master - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2021-10-13 - **Last Updated**: 2021-10-13 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README # 利用rayrender动态可视化全球人口密度 ## 介绍rayrender rayrender 是一个R语言编写的开源包,用于创建光线跟踪场景。这个包为用 C++ 构建的光线追踪器提供了一个整洁的 R API,以渲染由一组基元构建的场景。 rayrender 使用可管道化的迭代界面构建场景,并支持漫反射、金属、电介质(玻璃)、发光材料,以及程序和用户指定的图像纹理和 HDR 环境照明。 rayrender 包括通过 RcppThread 的多核支持(带有进度条)、通过 PCG RNG 的随机数生成以及通过 TinyObrjLoader 的 .obj 文件支持。 [Build and Raytrace 3D Scenes • rayrender](https://www.rayrender.net/) ## 数据源 NASA社会数据应用中心的世界格网人口数据V4版本,2010年30km级别数据 ### 下载链接 https://sedac.ciesin.columbia.edu/data/set/gpw-v4-basic-demographic-characteristics-rev11/data-download ## 可视化过程 1. 安装R语言环境 2. 安装rayrender,rayshader,rgdal,magick等包 3. 运行脚本 4. 利用Python脚本拼接单独生成的PNG格式的图片为GIF格式的图片,以作展示 ### 可视化脚本 ```R library(rayshader) library(rayrender) popdata = raster::raster("gpw_v4_basic_demographic_characteristics_rev11_atotpopbt_2010_dens_15_min.tif") population_mat = rayshader:::flipud(raster_to_matrix(popdata)) above1 = population_mat > 1 above5 = population_mat > 5 above10 = population_mat > 10 above50 = population_mat > 50 above100 = population_mat > 100 above500 = population_mat > 500 above1000 = population_mat > 1000 above1[is.na(above1)] = 0 above5[is.na(above5)] = 0 above10[is.na(above10)] = 0 above50[is.na(above50)] = 0 above100[is.na(above100)] = 0 above500[is.na(above500)] = 0 above1000[is.na(above1000)] = 0 turbocols = viridis::turbo(7) wc = 0.4 chart_items = xy_rect(x=-1,y=-1.4,z=1,xwidth=wc,ywidth=0.2, material=diffuse(color="grey30")) %>% add_object(text3d(label = "0", x=-1,y=-1.4,z=1.01, text_height = 0.1, material=diffuse(color="black"))) %>% add_object(xy_rect(x=-0.6,y=-1.4,z=1,xwidth=wc,ywidth=0.2, material=diffuse(color=turbocols[1]))) %>% add_object(text3d(label = "1>", x=-0.6,y=-1.4,z=1.01, text_height = 0.1, material=diffuse(color="black"))) %>% add_object(xy_rect(x=-0.2,y=-1.4,z=1,xwidth=wc,ywidth=0.2, material=diffuse(color=turbocols[2]))) %>% add_object(text3d(label = "5>", x=-0.2,y=-1.4,z=1.01, text_height = 0.1, material=diffuse(color="black"))) %>% add_object(xy_rect(x=0.2,y=-1.4,z=1,xwidth=wc,ywidth=0.2, material=diffuse(color=turbocols[3]))) %>% add_object(text3d(label = "10>", x=0.2,y=-1.4,z=1.01, text_height = 0.1, material=diffuse(color="black"))) %>% add_object(xy_rect(x=0.6,y=-1.4,z=1,xwidth=wc,ywidth=0.2, material=diffuse(color=turbocols[4]))) %>% add_object(text3d(label = "50>", x=0.6,y=-1.4,z=1.01, text_height = 0.1, material=diffuse(color="black"))) %>% add_object(xy_rect(x=1.0,y=-1.4,z=1,xwidth=wc,ywidth=0.2, material=diffuse(color=turbocols[5]))) %>% add_object(text3d(label = "100>", x=1.0,y=-1.4,z=1.01, text_height = 0.1, material=diffuse(color="black"))) %>% add_object(xy_rect(x=1.4,y=-1.4,z=1,xwidth=wc,ywidth=0.2, material=diffuse(color=turbocols[6]))) %>% add_object(text3d(label = "500>", x=1.4,y=-1.4,z=1.01, text_height = 0.1, material=diffuse(color="black"))) %>% add_object(xy_rect(x=1.8,y=-1.4,z=1,xwidth=wc,ywidth=0.2, material=diffuse(color=turbocols[7]))) %>% add_object(text3d(label = "1000>", x=1.8,y=-1.4,z=1.01, text_height = 0.1, material=diffuse(color="black"))) %>% add_object(text3d(label = "People per 30km^2", x=-0.55,y=-1.2,z=1.01, text_height = 0.15, material=diffuse(color="white"))) %>% group_objects(group_translate = c(-0.4,0,0),group_scale=c(0.85,0.85,0.85)) radm = 1.2 for(i in 1:720) { chart_items %>% add_object(group_objects( sphere(radius=0.99*radm,material=diffuse(color="grey20")) %>% add_object(sphere(radius=1.0*radm,material= diffuse(color=turbocols[1],alpha_texture = above1))) %>% add_object(sphere(radius=1.02*radm,material=diffuse(color=turbocols[2],alpha_texture = above5))) %>% add_object(sphere(radius=1.03*radm,material=diffuse(color=turbocols[3],alpha_texture = above10))) %>% add_object(sphere(radius=1.04*radm,material=diffuse(color=turbocols[4],alpha_texture = above50))) %>% add_object(sphere(radius=1.05*radm,material=diffuse(color=turbocols[5],alpha_texture = above100))) %>% add_object(sphere(radius=1.06*radm,material=diffuse(color=turbocols[6],alpha_texture = above500))) %>% add_object(sphere(radius=1.07*radm,material=diffuse(color=turbocols[7],alpha_texture = above1000))), group_angle = c(0,-i/2,0))) %>% add_object(sphere(y=10,z=5,radius=3,material=light(intensity = 20))) %>% add_object(sphere(y=0,z=20,radius=3,material=light(intensity = 20))) %>% render_scene(width=1000,height=1000,samples=128,rotate_env = 180,clamp_value = 10, aperture=0, filename=sprintf("worldpopfocus%i.png",i), lookat=c(0,-0.2,0)) } ``` ### 单帧生成的结果图 ![worldpopfocus1](F:\公众号\rayrender\worldpopfocus1.png) ### 利用Python脚本拼接多张PNG图像 ```python import imageio def create_gif(image_list, gif_name): frames = [] for image_name in image_list: frames.append(imageio.imread(image_name)) imageio.mimsave(gif_name, frames, 'GIF', duration=0.1) return def main(): image_list = ["rayrender\worldpopfocus" + str(x)+".png" for x in range(1, 200)] gif_name = 'rayrender\created_gif.gif' create_gif(image_list, gif_name) if __name__ == "__main__": main() ``` ### 动态可视化结果 ![created180-200](F:\公众号\rayrender\created180-200.gif) ## 总结 rayrender提供了非常方便简洁的调用方式,即可实现很强的光线渲染效果。在GIS领域,如何实现好的光线渲染效果是一个比较热门的研究方向,而rayrender的渲染结果就非常出色,可以用于数字地形渲染、动态制图等方向。 ## 代码仓库 https://gitee.com/cubics29/rayender-dynamic-visualization